Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 149 370 29 123 212 577 296 191 1 101 824 102 616 804 603 647 281 936 552 241
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 296 191 370 NA 149 1 647 NA 552 824 577 212 102 241 NA 804 281 936 603 616 29 123 101
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 2 4 1 5 3 4 2 1 5 2
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "w" "q" "r" "p" "m" "T" "H" "R" "E" "P"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 18
which( manyNumbersWithNA > 900 )
[1] 18
which( is.na( manyNumbersWithNA ) )
[1] 4 8 15
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 936
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 936
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 936
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "T" "H" "R" "E" "P"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "w" "q" "r" "p" "m"
manyNumbers %in% 300:600
[1] FALSE TRUE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[18] FALSE TRUE FALSE
which( manyNumbers %in% 300:600 )
[1] 2 6 19
sum( manyNumbers %in% 300:600 )
[1] 3
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "small" "small" NA "small" "small" "large" NA "large" "large" "large" "small" "small"
[14] "small" NA "large" "small" "large" "large" "large" "small" "small" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "small" "small" "UNKNOWN" "small" "small" "large" "UNKNOWN" "large" "large"
[11] "large" "small" "small" "small" "UNKNOWN" "large" "small" "large" "large" "large"
[21] "small" "small" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 0 0 NA 0 0 647 NA 552 824 577 0 0 0 NA 804 0 936 603 616 0 0 0
unique( duplicatedNumbers )
[1] 2 4 1 5 3
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 2 4 1 5 3
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 18
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 936
which.min( manyNumbersWithNA )
[1] 6
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 1
range( manyNumbersWithNA, na.rm = TRUE )
[1] 1 936
manyNumbersWithNA
[1] 296 191 370 NA 149 1 647 NA 552 824 577 212 102 241 NA 804 281 936 603 616 29 123 101
sort( manyNumbersWithNA )
[1] 1 29 101 102 123 149 191 212 241 281 296 370 552 577 603 616 647 804 824 936
sort( manyNumbersWithNA, na.last = TRUE )
[1] 1 29 101 102 123 149 191 212 241 281 296 370 552 577 603 616 647 804 824 936 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 936 824 804 647 616 603 577 552 370 296 281 241 212 191 149 123 102 101 29 1 NA NA NA
manyNumbersWithNA[1:5]
[1] 296 191 370 NA 149
order( manyNumbersWithNA[1:5] )
[1] 5 2 1 3 4
rank( manyNumbersWithNA[1:5] )
[1] 3 2 4 5 1
sort( mixedLetters )
[1] "E" "H" "m" "p" "P" "q" "r" "R" "T" "w"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 5.0 1.5 8.0 1.5 3.5 10.0 6.0 8.0 3.5 8.0
rank( manyDuplicates, ties.method = "min" )
[1] 5 1 7 1 3 10 6 7 3 7
rank( manyDuplicates, ties.method = "random" )
[1] 5 1 7 2 4 10 6 9 3 8
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.000000000 -0.500000000 0.000000000 0.500000000 1.000000000 0.602355239 -0.001790798 -1.110189415
[9] 1.370171605 1.558475351 0.437300171 -1.348139166 -0.716023738 -0.424224215 1.592424270
round( v, 0 )
[1] -1 0 0 0 1 1 0 -1 1 2 0 -1 -1 0 2
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.6 0.0 -1.1 1.4 1.6 0.4 -1.3 -0.7 -0.4 1.6
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.60 0.00 -1.11 1.37 1.56 0.44 -1.35 -0.72 -0.42 1.59
floor( v )
[1] -1 -1 0 0 1 0 -1 -2 1 1 0 -2 -1 -1 1
ceiling( v )
[1] -1 0 0 1 1 1 0 -1 2 2 1 -1 0 0 2
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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